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Artificial Intelligence: Retail & Marketing Issues

What Is AI?

Artificial Intelligence (AI) consists of implementing specific techniques allowing machines to imitate a form of natural intelligence. A scientific discipline invented in 1955, AI comprises algorithms and neural networks. We speak of strong AI when it applies to reproducing the functioning of a human brain and weak AI when it focuses on mastering a single task.

In summary, artificial intelligence isn’t an innovation by its own doing; however, a bunch of innovations and devices which permit information to be changed into savvy activities.AI is found in a growing number of application areas. If it holds a prominent place in the digital world, like the new Google Tacotron 2 voice, for example, it is indistinguishable from the human voice.

AI is also becoming more and more established in the world of Retail and marketing. 

It is about transforming the interactions between the customer and the product, that is to say, the customer journey, essential notions to identify the needs and desires of the consumer to define his purchasing behavior. AI would directly impact the buyer and his entire decision-making process: it represents a fundamental asset that must be used and will become essential to help companies streamline their processes and optimize the shopper experience through animations.

Virtual. Profit? Fewer returned items and better inventory management resulted in retailer savings and happy consumers. On the shopper side, the shopping experience will be smoother. For example, he will have seen clothes he likes on Pinterest or Facebook. By clicking on them, he can be directed to a retailer page where artificial intelligence will personalize this look according to the customer’s style.

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AI & Retail: A Transformed Shopper Experience With The Bringing Together Of The Physical And Digital Worlds

In the collective mind, the future is perceived as an era in which the digital and natural worlds will become one. When we think of shopping, it’s really about making decisions. The shopper doesn’t want new shopping experiences. They want better shopping experiences. The internet is ubiquitous, we cannot avoid it, but the web can serve as a lever to bring the shopper back to the store.

It is necessary to blur the lines between real and online shopping. E-commerce has changed our way of life. We are looking for what is easier, faster, and more entertaining. This is why brands must offer a coherent shopping experience in line with these new consumer trends.

AI & Drive To Store: Re-Enchanted In-Store Experience 

E-commerce only has some of the qualities required to satisfy the shopper fully, physical stores have their cards to play, but the shopping experience needs to be reflected. Retail has understood this well, and for several years now, exciting concepts have been emerging, such as, among others, fitting 2.0.

Virtual Fitting Rooms

Fitting is a critical moment in shopping. This is a practical step that differentiates the purchase in-store from the purchase on the internet. It allows you to see if a product fits you, to know if you feel good in a garment, and to collect valuable data. Take what’s best in e-commerce, and fix what’s uncomfortable in shopping. You will get the virtual (or interactive) fitting room. A concept that offers a new way of shopping, a mix between e-commerce and shopping.

The intuitive fitting room perceives the item when you enter the room, the model, the size, the variety, and the style. You do your fittings before the mirror, which adjusts every item to your morphology. She can offer you another by squeezing the advanced mirror screen if the article needs to measure up for you precisely. With these virtual lodges, you never again need to burn through 3/4 of an hour stripping down and afterward getting dressed again before finding THE outfit you like and suits you: an extensive, efficient device, an assurance of cleanliness, or, more each of them, a sporting encounter.

Facilitator Of Daily Life And Generator Of Customer Loyalty

The mix of physical and computerized (“phygital”) permits the client to encounter another shopping experience in the store. In this way, the brands offer clients the valuable chance to improve their excursion on the racks as per their shopping list (indoor geolocation), to lessen their holding up time at the checkout because of self-filtering and contactless installment innovations or yet-to-utilize dematerialized particular or faithfulness program… Nonetheless, merchants shouldn’t cease dispensing simply profound rationale to their associated store methodology.

AI & Digital: A Powerful Predictive Marketing Engine

Artificial intelligence undeniably perfects the analysis of the buyer. It delivers valuable clues about its behavior and provides more information and purchasing tools. AI is powered by data, the processing of which falls under a discipline called “machine learning.”

What Is Machine Learning?

The behavior of the shopper has deciphered thanks to the latter. Many artificial intelligence systems used in digital marketing and e-commerce are based, to a greater or lesser extent, on a learning capacity. The most recent trend within customer services is the integration of AI and predictive technologies, essentially to anticipate and solve customer problems before customers even detect them.

Predictive Analytics

Thanks to machine learning, we can perceive the intention of the consumer. His behavioral tendencies are captured and constantly optimized according to his actions. These transformations are just beginning in the marketing world, but AI will soon be able to predict your needs.


Machine learning is thus at the origin of advertising optimization algorithms or product recommendation engines. These refer to their history of actions and results to “learn” and optimize the creations, campaigns, or recommendations to follow. Do ads from your favorite brand appear when you browse Google? You have indeed visited his site recently. For example, the Spotify music platform also captures your musical affinities and tastes to create tailor-made playlists for its users.


The role of artificial intelligence is to reshape the canvas according to the buyer’s needs. It can forecast the consumer’s desires thanks to recommendation tools which multiply and are activated during browsing websites. However, the challenge is to continue developing these technologies to guide the buyer according to his emotions. The latter, initially picked up by ever more efficient products (smartphones, connected objects, etc.), will be able to offer and recommend an item suited to the buyer’s state of mind.


Google and its RankBrain algorithm also use machine learning to determine the best results for a search engine query. The concept of machine learning is also essential in the development and optimization of “chatbot” type tools. They allow brands to start a direct dialogue with customers, paving the way for marketing and sales. This is an excellent opportunity for brands to create personalized recommendations for the consumer based on insights gained from a series of conversations.